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Sensors  2013 

Wedge-Filtering of Geomorphologic Terrestrial Laser Scan Data

DOI: 10.3390/s130202579

Keywords: terrestrial laser scanning, filtering, wedge

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Abstract:

Terrestrial laser scanning is of increasing importance for surveying and hazard assessments. Digital terrain models are generated using the resultant data to analyze surface processes. In order to determine the terrain surface as precisely as possible, it is often necessary to filter out points that do not represent the terrain surface. Examples are vegetation, vehicles, and animals. Filtering in mountainous terrain is more difficult than in other topography types. Here, existing automatic filtering solutions are not acceptable, because they are usually designed for airborne scan data. The present article describes a method specifically suitable for filtering terrestrial laser scanning data. This method is based on the direct line of sight between the scanner and the measured point and the assumption that no other surface point can be located in the area above this connection line. This assumption is only true for terrestrial laser data, but not for airborne data. We present a comparison of the wedge filtering to a modified inverse distance filtering method (IDWMO) filtered point cloud data. Both methods use manually filtered surfaces as reference. The comparison shows that the mean error and root–mean-square-error (RSME) between the results and the manually filtered surface of the two methods are similar. A significantly higher number of points of the terrain surface could be preserved, however, using the wedge-filtering approach. Therefore, we suggest that wedge-filtering should be integrated as a further parameter into already existing filtering processes, but is not suited as a standalone solution so far.

References

[1]  ASPRS Guidelines–Vertical Accuracy Reporting for LiDAR Data. Available online: http://www.asprs.org/a/society/committees/lidar/Downloads/Vertical_Accuracy_Reporting_for_Lidar_Data.pdf (accessed on 1 February 2013).
[2]  Lindenberger, J. Laser-Profilmessungen Zur Topographischen Gel?ndeaufnahme. Ph.D. Thesis, Universit?t Stuttgart, Stuttgart, Germany, 1993.
[3]  Kilian, J.; Haala, N.; Englich, M. Capture and evaluation of airborne laser scanner data. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 1996, 31, 383–388.
[4]  Pfeifer, N.; K?stli, A.; Kraus, K. Interpolation and filtering of laser scanner data-implementation and first results. Int. Arch. Photogramm. Remote Sens. 1998, 32, 153–159.
[5]  Von Hansen, W.; V?gtle, T. Extraktion der gel?ndeoberfl?che aus flugzeuggetragenen laserscanner-aufnahmen. PFG 1999, 4, 299–236.
[6]  Axelsson, P. DEM generation from laser scanner data using adaptive TIN models. Int. Arch. Photogramm. Remote Sens. 2000, 33, 110–117.
[7]  Vosselman, G. Slope-based filtering of laser altimetry data. Int. Arch. Photogramm. Remote Sens. 2000, 33, 935–942.
[8]  Wack, R.; Wimmer, A. Digital terrain models from airborne laser scanner data—A grid based approach. Int. Arch. Photogramm. Remote Sens. 2002, 35, 293–296.
[9]  Sithole, G.; Vosselman, G. Experimental comparison of filter algorithms for bare-earth extraction from airborne laser scanning point clouds. ISPRS J. Photogramm. Remote Sens. 2004, 59, 85–101.
[10]  Briese, C.; Pfeiffer, N.; Dorninger, P. Applications of the robust interpolation for DTM determination. symposium der ISPRS-comm. Int. Arch. Photogramm. Remote Sens. 2002, 34, 55–61.
[11]  Evans, J.S.; Hudak, A.T. A multiscale curvature algorithm for classifying discrete return LiDAR in forested environments. IEEE Trans. Geosci. Remote Sens. 2007, 45, 1029–1038.
[12]  Lim, M.; Petley, D.N.; Rosser, N.J.; Allison, R.J.; Long, A.J.; Pybus, D. Combined digital photogrammetry and time-of-flight laser scanning for monitoring cliff evolution. Photogramm. Rec. 2006, 20, 109–129.
[13]  Jaboyedoff, M.; Metzger, R.; Oppikofer, T.; Couture, R.; Derron, M.H.; Locat, J.; Turmel, D. New Insight Techniques to Analyze Rock-Slope Relief Using DEM and 3D-Imaging Cloud Points: COLTOP-3D Software. In Rock Mechanics: Meeting Society's Challenges and Demands; Eberhardt, E., Stead, D., Morrison, T., Eds.; Taylor & Francis: London, UK, 2007; pp. 61–68.
[14]  Prokop, A.; Panholzer, H. Assessing the capability of terrestrial laser scanning for monitoring slow moving landslides. Nat. Hazards Earth Syst. Sci. 2009, 9, 1921–1928.
[15]  Akca, D. Matching of 3D surfaces and their intensities. ISPRS J. Photogramm. Remote Sens. 2007, 62, 112–121.
[16]  Biasion, A.; Bornaz, L.; Rinaudo, F. Laser Scanning Applications on Disaster Management. In Geo-information for Disaster Management; van Oosterom, P., Zlatanova, S., Fendel, E.M., Eds.; Springer Verlag: Berlin, Germany, 2005; pp. 19–33.
[17]  Lindenbergh, R.; Pfeifer, N. A Statistical Deformation Analysis of Two Epochs of Terrestrial Laser Data of a Lock. Proceedings of the 7th Optical 3-D Measurement Techniques, Vienna, Austria, 3–5 October 2005; pp. 61–70.
[18]  Abellán, A.; Jaboyedoff, M.; Oppikofer, T.; Vilaplana, J.M. Detection of millimetric deformation using a terrestrial laser scanner: Experiment and application to a rockfall event. Nat. Hazards Earth Syst. Sci. 2009, 9, 365–372.
[19]  ESRI Education Services. Interpolating Surfaces in ArcGIS Spatial Analyst. 2005. Available online: http://www.esri.com/news/arcuser/0704/files/interpolating.pdf (accessed on 20 October 2012).
[20]  Gianinetto, M.; Fassi, F. Validation of cartosat-1 DSM generation for the salon de provence test site. ISPRS J. Photogramm. Remote Sens. 2008, 37, 1369–1374.
[21]  H?hle, J.; H?hle, M. Accuracy assessment of digital elevation models by means of robust statistical methods. ISPRS J. Photogramm. Remote Sens. 2009, 64, 398–406.
[22]  Assessment of the Quality of Digital Terrain Models. Available online: http://www.eurosdr.net/publications/60.pdf (accessed on 1 February 2013).

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